期刊名称:International Journal of Software Engineering and Its Applications
印刷版ISSN:1738-9984
出版年度:2016
卷号:10
期号:10
页码:1-8
DOI:10.14257/ijseia.2016.10.10.01
出版社:SERSC
摘要:Image binarization is divided into global algorithm and local algorithm. Global binarization algorithms have a problem to describe objects that have similar brightness with a single threshold. Local binarization algor ithms make boundary lines because these algorithms split the image into a specific size of blocks. Therefo re, in this paper, we propose a binarization method to complement these problems. The proposed method uses triangular fuzzy membership function to cla ssify the image into obvious regions and ambiguous regions. Obvious regions are binarized by using global binarization algorithm. Whereas ambiguous regions are binarized by using improved local algorithm. Experimental results show the proposed method binar izes the image with less information loss. Moreover, binarized image describes the object in more detail than global binarization methods and more natural than local binarization method.
关键词:Image processing; Fuzzy Logic; Local Binarization; Image E ; nhancement; ; Improved Binarization